Genomics-based resources for model organisms have recently fuelled the development of various functional genomics approaches that all aim to accelerate our ability to understand gene function and map cellular pathways/protein complexes. Some of the most powerful global approaches are based on scaling up long- standing concepts in biology, i.e. epistasis/genetic interactions - how the function of one gene depends on the function of a second gene, and chemical genetic interactions - how the function of one gene affects cellular responses to chemical stress, finding a quantitative readout for them and devising ways to globally assess the data and maximize the extracted information. UCSF has played a pivotal role in the above process, perfecting the genetic interaction technology for S. cerevisiae and adding a new dimension to the biology that can be extracted from these methods. The highly collaborative and interactive research spirit that characterizes the school, and its optimized pipeline of state-of-the-art robotic equipment and complementary facilities make UCSF a unique place for extending these technologies to other organisms. Since I arrived at UCSF on a prestigious EMBO fellowship, I have led an effort to develop such methodologies for prokaryotes and apply them to infer mechanistic insights on their biology. The technology we recently published for E. coli was featured in two comment articles, and our current work on generating a systematic chemical genetic profiling of the entire E. coli genome and a comprehensive genetic interaction map for its envelope compartment is almost completed and contains numerous insights on new biology. Here, I propose to develop and implement equivalent technology for the first time in a model pathogenic micoorganism, S. typhimurium. Having comparable data in both E. coli and S. typhimurium will allow me to perform a seminal comprehensive cross-species study in prokaryotes and monitor how simple and closely related unicellular organisms adjust their networks to adapt to different lifestyles and meet the needs of versatile environments. This effort will be extended as tools and data for key gram-positive organisms become available. Being trained as a biochemist and molecular microbiologist in my undergraduate and graduate studies, I have become confident in tackling hypothesis-driven questions on mechanism in a variety of fields. I also have acquired important skills in systems biology in the past two years, but to assume a leadership role and be able to drive this field forward, I need additional training in bioinformatics/biostatistics and pathogenesis. For this I have organized a rigorous career development plan that includes: a) a selection of targeted coursework, b) a team of world-leading scientists with cutting-edge expertise on all possible aspects of this project as my advisory board and c) two inspiring mentors who have been helping me all along in my systems biology endeavors;their experience and guidance will both facilitate the progress of the proposed work and help me improve my personal skills as a group leader. A plethora of mechanistic inferences stemming out of the proposed work will serve as a jumping-off point for my own lab. I envision my independent investigator career being in the interface of systems biology and hypothesis-driven mechanistic research, bridging the two to improve our knowledge on various key-biological aspects such as membrane assembly, regulation of cell growth and division, signal transduction, transcriptional cascades, drug assimilation/side- effects and combinatorial use, and evolutionary adaptation. PUBLIC HEALTH RELEVANCE: Bacteria are among the simplest and at the same time most diverse organisms in nature. Here, we propose to build the first comprehensive picture of the functional network organization of a compartment that constitutes the bacterium's interface to the environment. Our efforts will be concentrated on two closely related organisms, S. typhimurium, the number one cause of food-borne illnesses in western countries, and a harmless "domesticated" E. coli strain. Comparisons between the two organisms will illuminate important aspects of bacterial evolution and pathogenesis, and the information can be used to understand the mode of action of novel drugs and improve therapy for bacterial disease.